CFOs, are your finance teams ready for AI?

Advancements in artificial intelligence (AI) technology hold the potential to provide CFOs with enhanced insights into their organisation’s financial performance and facilitate proactive planning. With analytical and predictive capabilities, AI tools are positioned to expedite critical processes like financial forecasting and planning. Consequently, integration of AI into financial operations is high on CFOs’ agenda.

Deloitte’s CFO Survey Spring shows that the use of AI for decision-making is on the rise with the percentage of decisions made using AI technologies set to increase from 13% to 39% over the next five years.

While the use of AI in finance promises augmented visibility into financial performance, implementing AI too quickly poses significant risks CFOs need to be aware of.

AI can transform the finance department

In the past year, businesses have dealt with challenges such as limited credit availability, high inflation and interest rates. CFOs and their financial departments have taken a greater role in formulating business strategies to overcome volatile market conditions and create business value.

Protecting an organisations’ financial position requires strategic planning to lower risk exposure and identify possible opportunities to bolster financial performance. For example, finance and treasury teams have been essential to securing cash flow and profitability by mitigating the consequences of unpredictable costs and FX.

Beyond automation, AI has the potential to transform how finance teams understand market movements and risk. With the ability to analyse and process vast amounts of data, AI algorithms can enhance predictive capabilities of CFOs and their teams. This will allow decisions about resource optimisation, and business growth to be forward-looking as deriving insights from data becomes more efficient with AI.

Financial forecasting is a process that stands to significantly benefit from AI as forecasting becomes more accurate due to the granularity of data analysis that can be executed. Finance teams can derive insights from individual customer behaviour to forecast revenue streams. Furthermore, when analysing the gap between forecasts and reality, AI will also increase the number of combinations that can be made to improve future forecasting significantly.

AI will help finance teams transform risk management strategies to meet the demands of the current financial landscape. Rapid changes in interest rates, currency fluctuations, commodities, and supply chain risks have created both risks and opportunities that CFOs need to pay attention to.

By processing millions of historical data points and accounting for multiple variables such as market trends, AI can identify patterns, correlations, and anomalies more efficiently than humans to create better visibility into an organisation’s risk posture. Finance teams can also automate certain processes such as FX aggregating requests, pricing request initiations, or executing trade strategies based on favourable pre-designed parameters to quickly mitigate risks or capitalise on opportunities from real-time data insights.

Is your finance department ready for AI? 

As has been the case with other emerging technologies, rushing into digital initiatives can have unwanted consequences that undermine productivity gains. CFOs need to interrogate the preparedness of their finance department for AI deployment to ensure they can build a strong business case for scaling AI adoption.

Ensuring data quality

An AI algorithm’s ability to learn and adapt is a major benefit as AI tools get more effective at their tasks by ingesting more and more data. However, if the data collection process results in inaccurate or insufficient data, the purpose of an AI model is defeated as it would not be able to learn and evolve. This is especially true for finance teams that require real-time data from numerous sources for informed decision-making.

Additionally, if not supervised, AI might be analysing data incorrectly and leading to wrong conclusions and predictions. CFOs have to ensure that the data collection processes within their organisations are optimised for quality data. Automation is a prerequisite for AI adoption as RPAs reduce the time taken to collect data and eliminate human errors.

Upskilling finance teams

AI implementation across any department requires employees to learn new skills on how best to utilise AI. Employees and management must fully understand the technology and how it can improve their day-to-day tasks to see positive results. Implementing AI too quickly may mean finance teams lack the skills and understanding required to avoid critical mistakes and consequences in using AI.

Additionally, without proper training, employees may feel threatened by the pace of new technology and are more likely to resist rapid changes. CFOs must find ways to keep human interests at the centre of AI implementation through upskilling initiatives that help employees become more efficient using AI. Securing employee buy-in will also allow AI initiatives to scale throughout the department.

Governance issues

CFOs need to oversee the establishment of governance processes within the finance department to ensure AI is yielding positive results and not unwanted consequences.

This would entail reviewing processes and creating new ones that govern how AI is used in automation by continuously testing AI systems, fine-tuning how AI is applied, restricting use cases, and keeping humans at the centre. Aligning stakeholders on the goals of AI and automation initiatives requires proper governance and processes that push stakeholders to work together towards these goals.

Transformation potential

AI is a seriously impressive technology that will transform finance processes and how organisations approach risk management. But the stakes for not getting the AI recipe right are high. Especially within finance departments where the well-being of an organisation rests on the ability of teams to predict financial conditions accurately.

That is why CFOs must lay the groundwork and ensure their processes are fully optimised before rushing into AI adoption. A cautionary approach that interrogates the readiness of finance departments to embrace AI will give decision-makers insights to navigate uncertain economic times and lead their organisations to strong financial performance.

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